Goedkoop, Willem
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
Research article2018Peer reviewed
Schell, Theresa; Goedkoop, Willem; Zubrod, Jochen P.; Feckler, Alexander; Luederwald, Simon; Schulz, Ralf; Bundschuh, Mirco
The environmental risk assessment of pesticides is mainly performed on individual active ingredients. In surface waters within the agricultural landscape, however, contamination is usually characterized by complex pesticide mixtures. To estimate the joint effects caused by these complex mixtures, mathematical models have been proposed. Among these, the model of concentration addition (CA) is suggested as default model for the risk assessment of chemical mixtures as it is considered protective for mixtures composed of similar and dissimilar acting substances. Here we assessed the suitability of CA predictions for seven field relevant pesticide mixtures using acute (immobility) and chronic (reproduction) responses of the standard test species Daphnia magna. Pesticide mixtures indicated largely additive or less than additive effects when using CA model predictions as a reference. Moreover, we revealed that deviations from CA predictions are lower for chronic (up to 3.2-fold) relative to acute (up to 7.2-fold) response variables. Additionally, CA predictions were in general more accurate for complex mixtures relative to those composed of only a few pesticides. Thus, this study suggests CA models as largely protective for the risk assessment of pesticide mixtures justifying its use as default model. At the same time, extrapolating conclusions about the joint effects of pesticides from acute to chronic responses is uncertain, due to partly large discrepancies with regards to the deviation of model prediction and observed effects between exposure scenarios. (C) 2018 Elsevier B.V. All rights reserved.
Mixture toxicity; Pesticide; Mode of toxic action; Concentration addition; Daphnia
Science of the Total Environment
2018, Volume: 644, pages: 342-349 Publisher: ELSEVIER SCIENCE BV
SDG3 Good health and well-being
SDG6 Clean water and sanitation
Environmental Sciences related to Agriculture and Land-use
DOI: https://doi.org/10.1016/j.scitotenv.2018.06.334
https://res.slu.se/id/publ/96748